IDEAS home Printed from https://ideas.repec.org/a/taf/amstat/v72y2018i2p140-146.html
   My bibliography  Save this article

A Note on Collinearity Diagnostics and Centering

Author

Listed:
  • Santiago Velilla

Abstract

The usual approach for diagnosing collinearity proceeds by centering and standardizing the regressors. The sample correlation matrix of the predictors is then the basic tool for describing approximate linear combinations that may distort the conclusions of a standard least-square analysis. However, as indicated by several authors, centering may eventually fail to detect the sources of ill-conditioning. In spite of this earlier claim, there does not seem to be in the literature a fully clear explanation of the reasons for this bad potential behavior of the traditional strategy for analyzing collinearity. This note studies this issue in some detail. Results derived are motivated by the analysis of a well-known real dataset. Practical conclusions are illustrated with several examples.

Suggested Citation

  • Santiago Velilla, 2018. "A Note on Collinearity Diagnostics and Centering," The American Statistician, Taylor & Francis Journals, vol. 72(2), pages 140-146, April.
    • Handle: RePEc:taf:amstat:v:72:y:2018:i:2:p:140-146
    DOI: 10.1080/00031305.2016.1264312
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00031305.2016.1264312
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00031305.2016.1264312?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. David A. Belsley, 1987. "Well-Conditioned Collinearity Indices?," Boston College Working Papers in Economics 132, Boston College Department of Economics.
    2. Raj Echambadi & James D. Hess, 2007. "Mean-Centering Does Not Alleviate Collinearity Problems in Moderated Multiple Regression Models," Marketing Science, INFORMS, vol. 26(3), pages 438-445, 05-06.
    3. Donald R. Jensen & Donald E. Ramirez, 2008. "Anomalies in the Foundations of Ridge Regression," International Statistical Review, International Statistical Institute, vol. 76(1), pages 89-105, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Román Salmerón-Gómez & Ainara Rodríguez-Sánchez & Catalina García-García, 2020. "Diagnosis and quantification of the non-essential collinearity," Computational Statistics, Springer, vol. 35(2), pages 647-666, June.
    2. Román Salmerón Gómez & Catalina García García & José García Pérez, 2020. "Detection of Near-Nulticollinearity through Centered and Noncentered Regression," Mathematics, MDPI, vol. 8(6), pages 1-17, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Claudia García-García & Catalina B. García-García & Román Salmerón, 2021. "Confronting collinearity in environmental regression models: evidence from world data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 895-926, September.
    2. Schilling, Melissa A. & Green, Elad, 2011. "Recombinant search and breakthrough idea generation: An analysis of high impact papers in the social sciences," Research Policy, Elsevier, vol. 40(10), pages 1321-1331.
    3. R. Salmerón & J. García & C. B. García & M. M. López Martín, 2017. "A note about the corrected VIF," Statistical Papers, Springer, vol. 58(3), pages 929-945, September.
    4. Jing Zhang & Justin Tan & Poh Wong, 2015. "When does investment in political ties improve firm performance? The contingent effect of innovation activities," Asia Pacific Journal of Management, Springer, vol. 32(2), pages 363-387, June.
    5. Thaddeus Neururer & George Papadakis & Edward J. Riedl, 2016. "Tests of investor learning models using earnings innovations and implied volatilities," Review of Accounting Studies, Springer, vol. 21(2), pages 400-437, June.
    6. Alex Eapen & Rekha Krishnan, 2019. "Transferring Tacit Know-How: Do Opportunism Safeguards Matter for Firm Boundary Decisions?," Organization Science, INFORMS, vol. 30(4), pages 715-734, July.
    7. Nicolas A. Zacharias & Ruth Maria Stock & Subin Im, 2017. "Strategic Givens In New Product Development: Understanding Curvilinear Effects On New Product Performance," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 21(01), pages 1-31, January.
    8. Alexis Lazaridis, 2007. "A Note Regarding the Condition Number: The Case of Spurious and Latent Multicollinearity," Quality & Quantity: International Journal of Methodology, Springer, vol. 41(1), pages 123-135, February.
    9. Lihong Qian & Rajshree Agarwal & Glenn Hoetker, 2012. "Configuration of Value Chain Activities: The Effect of Pre-Entry Capabilities, Transaction Hazards, and Industry Evolution on Decisions to Internalize," Organization Science, INFORMS, vol. 23(5), pages 1330-1349, October.
    10. Marina Anna Schmitz & Fabian Jintae Froese & Anna Katharina Bader, 2018. "Organizational cynicism in multinational corporations in China," Asia Pacific Business Review, Taylor & Francis Journals, vol. 24(5), pages 620-637, October.
    11. Moumen, Néjia & Ben Othman, Hakim & Hussainey, Khaled, 2015. "The value relevance of risk disclosure in annual reports: Evidence from MENA emerging markets," Research in International Business and Finance, Elsevier, vol. 34(C), pages 177-204.
    12. Vivian Zheng, Xu & Jenny Ji, Li & Su, Chenting, 2020. "Mitigating the Negative Effects of Regional Clustering in Franchising: The Roles of Governance Mechanisms," Journal of Retailing, Elsevier, vol. 96(3), pages 434-444.
    13. Kim Wang, 2017. "Technology Deployment By Late Movers," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 21(04), pages 1-25, May.
    14. Yi Liu & Tiezhu Shi & Zeying Lan & Kai Guo & Dachang Zhuang & Xiangyang Zhang & Xiaojin Liang & Tianqi Qiu & Shengfei Zhang & Yiyun Chen, 2024. "Estimating the Soil Copper Content of Urban Land in a Megacity Using Piecewise Spectral Pretreatment," Land, MDPI, vol. 13(4), pages 1-21, April.
    15. Burks, Jeffrey J. & Randolph, David W. & Seida, Jim A., 2019. "Modeling and interpreting regressions with interactions," Journal of Accounting Literature, Elsevier, vol. 42(C), pages 61-79.
    16. Wang, I. Kim & Seidle, Russell, 2017. "The degree of technological innovation: A demand heterogeneity perspective," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 166-177.
    17. Adomako, Samuel & Amankwah-Amoah, Joseph & Chu, Irene, 2020. "Entrepreneurs’ passion, home country’s institutional voids and small firm internationalization," Research in International Business and Finance, Elsevier, vol. 53(C).
    18. Ganesh Pillai, Rajani & Bindroo, Vishal, 2014. "The moderating roles of perceived complementarity and substitutability on the perceived manufacturing difficulty–extension attitude relationship," Journal of Business Research, Elsevier, vol. 67(7), pages 1353-1359.
    19. Jose Arias-Pérez & Geovanny Perdomo-Charry & Carlos Castaño-Ríos, 2017. "Not-Invented-Here Syndrome And Innovation Performance: The Confounding Effect Of Innovation Capabilities As Organisational Routines In Service Firms," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 21(01), pages 1-20, January.
    20. Homburg, Christian & Kuehnl, Christina, 2014. "Is the more always better? A comparative study of internal and external integration practices in new product and new service development," Journal of Business Research, Elsevier, vol. 67(7), pages 1360-1367.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:amstat:v:72:y:2018:i:2:p:140-146. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UTAS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.